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Where and what: Using smartphones to predict next locations and applications in daily life., and . Pervasive Mob. Comput., (2014)Improved Handwriting Recognition by Combining Two Forms of Hidden Markov Models and a Recurrent Neural Network., , , , , and . CAIP, volume 5702 of Lecture Notes in Computer Science, page 189-196. Springer, (2009)A Fast Method for Training Linear SVM in the Primal, and . (2008)Optimisation du Primal pour les SVM., and . EGC, volume RNTI-E-11 of Revue des Nouvelles Technologies de l'Information, page 273-284. Cépaduès-Éditions, (2008)Contextual conditional models for smartphone-based human mobility prediction., and . UbiComp, page 163-172. ACM, (2012)Polynomial Conditional Random Fields for Signal Processing., and . ECAI, volume 141 of Frontiers in Artificial Intelligence and Applications, page 797-798. IOS Press, (2006)Vlogging Over Time: Longitudinal Impressions and Behavior in YouTube., , , , and . MUM, page 37-46. ACM, (2018)Neural conditional random fields., and . AISTATS, volume 9 of JMLR Proceedings, page 177-184. JMLR.org, (2010)Maximum Margin Training of Gaussian HMMs for Handwriting Recognition., and . ICDAR, page 976-980. IEEE Computer Society, (2009)Contextual Grouping: Discovering Real-Life Interaction Types from Longitudinal Bluetooth Data., and . Mobile Data Management (1), page 256-265. IEEE Computer Society, (2011)